实验三SPSS多元时间序列分析方法.

　 实验三 多元时间序列分析方法

　实验目的了解协整理论及协整检验方法；掌握协整的两种检验方法：E-G两步法与Johansen方法；熟悉向量自回归模型VAR的应用；掌握误差修正模型ECM的含义及检验方法；掌握Granger因果关系检验方法。

　实验仪器

　装有EViews7.0软件的微机一台。

　实验内容

　【例6-2】

　时间与M2之间的关系首先用单位根检验是否为平稳序列。原假设为H0：非平稳序列 H1：平稳序列。用Eviews软件解决该问题，得到如下结果：

　Null Hypothesis: M2 has a unit root Exogenous: None Lag Length: 3 (Automatic - based on SIC, maxlag=13) t-Statistic Prob.* Augmented Dickey-Fuller test statistic ?5.681169 ?1.0000 Test critical values: 1% level -2.579052 5% level -1.942768 10% level -1.615423 *MacKinnon (1996) one-sided p-values. Augmented Dickey-Fuller Test Equation Dependent Variable: D(M2) Method: Least Squares Date: 04/16/13 Time: 10:36 Sample (adjusted): 1991M05 2005M01 Included observations: 165 after adjustments Variable Coefficient Std. Error t-Statistic Prob. M2(-1) 0.013514 0.002379 5.681169 0.0000 D(M2(-1)) -0.490280 0.074458 -6.584611 0.0000 D(M2(-2)) 0.070618 0.083790 0.842797 0.4006 D(M2(-3)) 0.387086 0.073788 5.245935 0.0000 R-squared 0.480147 ?Mean dependent var 1440.037 Adjusted R-squared 0.470461 ?S.D. dependent var 1509.489 S.E. of regression 1098.447 ?Akaike info criterion 16.86513 Sum squared resid 1.94E+08 ?Schwarz criterion 16.94042 Log likelihood -1387.373 ?Hannan-Quinn criter. 16.89569 Durbin-Watson stat 1.965242 从上图我们可以看出t-statistic的值是5.681169，大于临界值，p>a，故不能拒绝被检验的指数序列是非平稳的原假设。因此一阶差分序列进行ADF检验，结果如下图显示。

　Null Hypothesis: D(M2) has a unit root Exogenous: None Lag Length: 8 (Automatic - based on SIC, maxlag=13) t-Statistic Prob.* Augmented Dickey-Fuller test statistic ?0.988183 ?0.9143 Test critical values: 1% level -2.579587 5% level -1.942843 10% level -1.615376 *MacKinnon (1996) one-sided p-values. Augmented Dickey-Fuller Test Equation Dependent Variable: D(M2,2) Method: Least Squares Date: 04/16/13 Time: 10:37 Sample (adjusted): 1991M11 2005M01 Included observations: 159 after adjustments Variable Coefficient Std. Error t-Statistic Prob. D(M2(-1)) 0.053616 0.054257 0.988183 0.3247 D(M2(-1),2) -1.526069 0.096352 -15.83852 0.0000 D(M2(-2),2) -1.519649 0.149134 -10.18981 0.0000 D(M2(-3),2) -1.225623 0.184003 -6.660869 0.0000 D(M2(-4),2) -1.237445 0.196285 -6.304319 0.0000 D(M2(-5),2) -0.972024 0.197161 -4.930093 0.0000 D(M2(-6),2) -0.810098 0.185290 -4.372060 0.0000 D(M2(-7),2) -0.605069 0.144997 -4.172983 0.0001 D(M2(-8),2) -0.333781 0.080550 -4.143781 0.0001 R-squared 0.801713 ?Mean dependent var 16.07001 Adjusted R-squared 0.791137 ?S.D. dependent var 2352.919 S.E. of regression 1075.320 ?Akaike info criterion 16.85356 Sum squared resid 1.73E+08 ?Schwarz criterion 17.02727 Log likelihood -1330.858 ?Hannan-Quinn criter. 16.92410 Durbin-Watson stat 1.970407 从上图我们可以看出t-statistic的值是0.988183，大于临界值，p>a，故不能拒绝被检验的指数序列是非平稳的原假设。因此二阶差分序列进行ADF检验，结果如下图显示

　Null Hypothesis: D(M2,2) has a unit root Exogenous: None Lag Length: 7 (Automatic - based on SIC, maxlag=13) t-Statistic Prob.* Augmented Dickey-Fuller test statistic -9.223132 ?0.0000 Test critical values: 1% level -2.579587 5% level -1.942843 10% level -1.615376 *MacKinnon (1996) one-sided p-values. Augmented Dickey-Fuller Test Equation Dependent Variable: D(M2,3) Method: Least Squares Date: 04/16/13 Time: 10:38 Sample (adjusted): 1991M11 2005M01 Included observations: 159 after adjustments Variable Coefficient Std. Error t-Statistic Prob. D(M2(-1),2) -8.900755 0.965047 -9.223132 0.0000 D(M2(-1),3) 6.431129 0.924672 6.955038 0.0000 D(M2(-2),3) 4.970286 0.833541 5.962861 0.0000 D(M2(-3),3) 3.802432 0.700773 5.426055 0.0000 D(M2(-4),3) 2.617058 0.544596 4.805501 0.0000 D(M2(-5),3) 1.688201 0.380559 4.436109 0.0000 D(M2(-6),3) 0.910968 0.214990 4.237257 0.0000 D(M2(-7),3) 0.325934 0.080151 4.066487 0.0001 R-squared 0.941321 ?Mean dependent var 0.112057 Adjusted R-squared 0.938601 ?S.D. dependent var 4339.324 S.E. of regression 1075.236 ?Akaike info criterion 16.84747 Sum squared resid 1.75E+08 ?Schwarz criterion 17.00188 Log likelihood -1331.374 ?Hannan-Quinn criter. 16.91018 Durbin-Watson stat 1.963915 从上图我们可以看出t-statistic的值是-9.223132，小于临界值，p<a，故拒绝被检验的指数序列是平稳的原假设。

　

　Null Hypothesis: DDM2 has a unit root Exogenous: None Lag Length: 7 (Automatic - based on SIC, maxlag=13) t-Statistic Prob.* Augmented Dickey-Fuller test statistic -9.223132 ?0.0000 Test critical values: 1% level -2.579587 5% level -1.942843 10% level -1.615376 *MacKinnon (1996) one-sided p-values. Augmented Dickey-Fuller Test Equation Dependent Variable: D(DDM2) Method: Least Squares Date: 04/16/13 Time: 10:41 Sample (adjusted): 1991M11 2005M01 Included observations: 159 after adjustments Variable Coefficient Std. Error t-Statistic Prob. DDM2(-1) -8.900755 0.965047 -9.223132 0.0000 D(DDM2(-1)) 6.431129 0.924672 6.955038 0.0000 D(DDM2(-2)) 4.970286 0.833541 5.962861 0.0000 D(DDM2(-3)) 3.802432 0.700773 5.426055 0.0000 D(DDM2(-4)) 2.617058 0.544596 4.805501 0.0000 D(DDM2(-5)) 1.688201 0.380559 4.436109 0.0000 D(DDM2(-6)) 0.910968 0.214990 4.237257 0.0000 D(DDM2(-7)) 0.325934 0.080151 4.066487 0.0001 R-squared 0.941321 ?Mean dependent var 0.112057 Adjusted R-squared 0.938601 ?S.D. dependent var 4339.324 S.E. of regression 1075.236 ?Akaike info criterion 16.84747 Sum squared resid 1.75E+08 ?Schwarz criterion 17.00188 Log likelihood -1331.374 ?Hannan-Quinn criter. 16.91018 Durbin-Watson stat 1.963915

　

　Dependent Variable: DDM2 Method: Least Squares Date: 04/16/13 Time: 10:47 Sample (adjusted): 1991M05 2005M01 Included observations: 165 after adjustments Convergence achieved after 50 iterations MA Backcast: 1990M12 1991M04 Variable Coefficient Std. Error t-Statistic Prob. C 14.44319 10.74065 1.344723 0.1807 AR(1) -0.995579 0.055305 -18.00153 0.0000 AR(2) -0.837713 0.047357 -17.68914 0.0000 MA(1) -0.436708 0.096208 -4.539223 0.0000 MA(2) 0.175063 0.104359 1.677513 0.0954 MA(3) -0.880075 0.052403 -16.79446 0.0000 MA(4) 0.322618 0.100005 3.226012 0.0015 MA(5) 0.190454 0.096508 1.973453 0.0502 R-squared 0.805361 ?Mean dependent var 16.34363 Adjusted R-squared 0.796682 ?S.D. dependent var 2309.544 S.E. of regression 1041.391 ?Akaike info criterion 16.78177 Sum squared resid 1.70E+08 ?Schwarz criterion 16.93236 Log likelihood -1376.496 ?Hannan-Quinn criter. 16.84290 F-statistic 92.80278 ?Durbin-Watson stat 2.041303 Prob(F-statistic) 0.000000 Inverted AR Roots -.50+.77i ?-.50-.77i Inverted MA Roots ?.77+.22i .77-.22i ?-.30 -.40-.91i -.40+.91i

　【P127 例4-3】

　本案例的数据为联通股票的日股价序列，期限为2003年1月2日至2006年9月15日，共886个样本观测量。对其进行单位根检验，结果如下：

　Null Hypothesis: X has a unit root Exogenous: None Lag Length: 0 (Automatic - based on SIC, maxlag=20) t-Statistic Prob.* Augmented Dickey-Fuller test statistic ?0.076005 ?0.7067 Test critical values: 1% level -2.567575 5% level -1.941181 10% level -1.616459 *MacKinnon (1996) one-sided p-values. Augmented Dickey-Fuller Test Equation Dependent Variable: D(X) Method: Least Squares Date: 04/16/13 Time: 10:53 Sample (adjusted): 1/03/2003 9/14/2006 Included observations: 886 after adjustments Variable Coefficient Std. Error t-Statistic Prob. X(-1) 4.71E-05 0.000619 0.076005 0.9394 R-squared -0.000167 ?Mean dependent var 0.000587 Adjusted R-squared -0.000167 ?S.D. dependent var 0.044573 S.E. of regression 0.044577 ?Akaike info criterion -3.382071 Sum squared resid 1.758589 ?Schwarz criterion -3.376668 Log likelihood 1499.257 ?Hannan-Quinn criter. -3.380006 Durbin-Watson stat 2.014381 从上图我们可以看出t-statistic的值是?0.076005，大于临界值，p>a，故不能拒绝被检验的指数序列是非平稳的原假设。因此一阶差分序列进行ADF检验，结果如下图显示。

　Null Hypothesis: D(X) has a unit root Exogenous: None Lag Length: 0 (Automatic - based on SIC, maxlag=20) t-Statistic Prob.* Augmented Dickey-Fuller test statistic -29.94678 ?0.0000 Test critical values: 1% level -2.567578 5% level -1.941181 10% level -1.616459 *MacKinnon (1996) one-sided p-values. Augmented Dickey-Fuller Test Equation Dependent Variable: D(X,2) Method: Least Squares Date: 04/16/13 Time: 10:54 Sample (adjusted): 1/06/2003 9/14/2006 Included observations: 885 after adjustments Variable Coefficient Std. Error t-Statistic Prob. D(X(-1)) -1.007165 0.033632 -29.94678 0.0000 R-squared 0.503597 ?Mean dependent var -1.13E-05 Adjusted R-squared 0.503597 ?S.D. dependent var 0.063302 S.E. of regression 0.044600 ?Akaike info criterion -3.381041 Sum squared resid 1.758410 ?Schwarz criterion -3.375633 Log likelihood 1497.111 ?Hannan-Quinn criter. -3.378974 Durbin-Watson stat 1.999816 从上图我们可以看出t-statistic的值是-29.94678，远小于临界值，p<a，故拒绝被检验的指数序列是平稳的原假设。

　Dependent Variable: X Method: Least Squares Date: 04/16/13 Time: 11:00 Sample (adjusted): 1/03/2003 9/14/2006 Included observations: 886 after adjustments Convergence achieved after 4 iterations Variable Coefficient Std. Error t-Statistic Prob. C 2.466771 0.208973 11.80427 0.0000 AR(1) 0.992697 0.003809 260.6088 0.0000 R-squared 0.987151 ?Mean dependent var 2.386998 Adjusted R-squared 0.987137 ?S.D. dependent var 0.392414 S.E. of regression 0.044506 ?Akaike info criterion -3.384131 Sum squared resid 1.751013 ?Schwarz criterion -3.373325 Log likelihood 1501.170 ?Hannan-Quinn criter. -3.380000 F-statistic 67916.95 ?Durbin-Watson stat 2.008279 Prob(F-statistic) 0.000000 Inverted AR Roots .99

　四、实验心得

　通过这次的实验我感觉自己的水平还是很有限的，感觉实际操作中有很多的不足，课后自己也重新试过，感觉有很多还是没记住，但是在这次的实验中自己也有懂得了更多

　

相关关键词： 多元时间序列分析案例